Building Real-Time Video AI Applications Assesments

Accelerated Computing Intelligent Video Analytics DeepStream SDK
1

Hi, I’m doing this courses Course Detail | NVIDIA

The assesment is just edit in the FIXME part.
Here the error I encountered:

Error: gst-library-error-quark: Configuration file parsing failed (5): gstnvinfer.cpp(794): gst_nvinfer_start (): /GstPipeline:pipeline0/GstNvInfer:primary-inference:
Config file path: pgie_config_dashcamnet.txt

My whole code:

4.2

#Import necessary libraries
import sys
import gi
gi.require_version(‘Gst’, ‘1.0’)
from gi.repository import GObject, Gst, GLib
from common.bus_call import bus_call
import pyds

def run(input_file_path):
global inference_output
inference_output=
Gst.init(None)

# Create element that will form a pipeline
print("Creating Pipeline")
pipeline=Gst.Pipeline()

# source=Gst.ElementFactory.make(<<<<FIXME>>>>, "file-source") 
# source.set_property('location', <<<<FIXME>>>>)
# h264parser=Gst.ElementFactory.make(<<<<FIXME>>>>, "h264-parser")
source = Gst.ElementFactory.make("filesrc", "file-source")
source.set_property('location', input_file_path)
h264parser=Gst.ElementFactory.make("h264parse", "h264-parser")
decoder=Gst.ElementFactory.make("nvv4l2decoder", "nvv4l2-decoder")

# streammux=Gst.ElementFactory.make(<<<<FIXME>>>>, "Stream-muxer")    
# streammux.set_property('width', <<<<FIXME>>>>)
# streammux.set_property('height', <<<<FIXME>>>>)
# streammux.set_property('batch-size', <<<<FIXME>>>>)
streammux=Gst.ElementFactory.make("nvstreammux", "Stream-muxer")    
streammux.set_property('width', 720)
streammux.set_property('height', 1280)
streammux.set_property('batch-size', 1)

# pgie=Gst.ElementFactory.make(<<<<FIXME>>>>, "primary-inference")
pgie = Gst.ElementFactory.make("nvinfer", "primary-inference")
pgie.set_property('config-file-path', 'pgie_config_dashcamnet.txt')

nvvidconv1=Gst.ElementFactory.make("nvvideoconvert", "convertor")
# nvosd=Gst.ElementFactory.make(<<<<FIXME>>>>, "onscreendisplay")
nvosd=Gst.ElementFactory.make("nvdsosd", "onscreendisplay")
nvvidconv2=Gst.ElementFactory.make("nvvideoconvert", "convertor2")
capsfilter=Gst.ElementFactory.make("capsfilter", "capsfilter")
caps=Gst.Caps.from_string("video/x-raw, format=I420")
capsfilter.set_property("caps", caps)

encoder=Gst.ElementFactory.make("avenc_mpeg4", "encoder")
encoder.set_property("bitrate", 2000000)

# sink=Gst.ElementFactory.make(<<<<FIXME>>>>, 'filesink')
sink=Gst.ElementFactory.make("filesink", 'filesink')
sink.set_property('location', 'output.mpeg4')
sink.set_property("sync", 1)

# Add the elements to the pipeline
print("Adding elements to Pipeline")
pipeline.add(source)
pipeline.add(h264parser)
pipeline.add(decoder)
pipeline.add(streammux)
pipeline.add(pgie)
# pipeline.add(<<<<FIXME>>>>)
pipeline.add(nvvidconv1)
pipeline.add(nvosd)
pipeline.add(nvvidconv2)
pipeline.add(capsfilter)
pipeline.add(encoder)
pipeline.add(sink)

# Link the elements together
print("Linking elements in the Pipeline")
source.link(h264parser)
h264parser.link(decoder)
decoder.get_static_pad('src').link(streammux.get_request_pad("sink_0"))
# streammux.link(<<<<FIXME>>>>)
# <<<<FIXME>>>>.link(nvvidconv1)
# nvvidconv1.link(<<<<FIXME>>>>)
# <<<<FIXME>>>>.link(nvvidconv2)
streammux.link(nvvidconv1)
nvvidconv1.link(nvvidconv2)
nvvidconv2.link(capsfilter)
capsfilter.link(encoder)
nvvidconv2.link(capsfilter)
capsfilter.link(encoder)
encoder.link(sink)

# Attach probe to OSD sink pad
osdsinkpad=nvosd.get_static_pad("sink")
# <<<<FIXME>>>>.add_probe(Gst.PadProbeType.BUFFER, <<<<FIXME>>>>, 0)
osdsinkpad.add_probe(Gst.PadProbeType.BUFFER, osd_sink_pad_buffer_probe, 0)

# Create an event loop and feed gstreamer bus mesages to it
loop=GLib.MainLoop()
bus=pipeline.get_bus()
bus.add_signal_watch()
bus.connect("message", bus_call, loop)

# Start play back and listen to events
print("Starting pipeline")

pipeline.set_state(Gst.State.PLAYING)
try:
    loop.run()
except:
    pass

pipeline.set_state(Gst.State.NULL)
return inference_output

By the way, I got 0/20 in the assesment marks, I dont think I get all them incorrect so I dont think the answer is saved.

3

The “pgie_config_dashcamnet.txt” content is wrong.

4

I have remove it and put the file where it belong but still got the same error

5

The log just says the config file is wrong. Please check it.

The better choice is to study Welcome to the DeepStream Documentation — DeepStream documentation 6.4 documentation and run deepstream-test1.

6

I still dont understand what the error here
“Error: gst-library-error-quark: Configuration file not provided (5): gstnvinfer.cpp(788): gst_nvinfer_start (): /GstPipeline:pipeline5/GstNvInfer:primary-inference”

7

The gst-nvinfer does not find the configured configuration file.

8

You set the configuration file here, but the file is not in the same folder of your python app.

9

There is python samples: NVIDIA-AI-IOT/deepstream_python_apps: DeepStream SDK Python bindings and sample applications (github.com)

Please refer to the samples.

10

There is no update from you for a period, assuming this is not an issue anymore. Hence we are closing this topic. If need further support, please open a new one. Thanks

11

This topic was automatically closed 14 days after the last reply. New replies are no longer allowed.